Note: Supplemental materials are not guaranteed with Rental or Used book purchases.
Purchase Benefits
Looking to rent a book? Rent End-to-End Adaptive Congestion Control in TCP/IP Networks [ISBN: 9781439840573] for the semester, quarter, and short term or search our site for other textbooks by Houmkozlis; Christos N.. Renting a textbook can save you up to 90% from the cost of buying.
List of Figures | p. xiii |
List of Tables | p. xix |
Preface | p. xxi |
Introduction | p. 1 |
Overview | p. 1 |
Future Internet | p. 2 |
Internet Congestion Control | p. 4 |
Adaptive Congestion Control | p. 8 |
Background on Computer Networks and Congestion Control | p. 13 |
Controlled System: The Packet-Switched Network | p. 15 |
Overview | p. 15 |
Network Connectivity | p. 17 |
Links and Nodes | p. 17 |
Sub-Networks | p. 17 |
Network Classification | p. 19 |
LAN Topologies | p. 21 |
Network Communication | p. 24 |
Packet Switching | p. 24 |
Protocols and Layering | p. 26 |
Internet Architecture | p. 28 |
Transfer Control Protocol (TCP) | p. 32 |
User Datagram Protocol (UDP) | p. 37 |
Internet Protocol (IP) | p. 38 |
Performance Characteristics | p. 40 |
Queue Size | p. 40 |
Throughput | p. 41 |
Link Utilization | p. 41 |
Packet Loss Rate | p. 41 |
Round Trip Time | p. 41 |
Fairness | p. 42 |
Applications | p. 43 |
p. 44 | |
World Wide Web | p. 44 |
Remote Access | p. 45 |
File Transfer | p. 45 |
Streaming Media | p. 46 |
Internet Telephony (VOIP) | p. 46 |
Concluding Comments | p. 47 |
Congestion Issues and TCP | p. 49 |
Overview | p. 49 |
Core Issues in Congestion Control | p. 50 |
TCP: Flow Control and Congestion Control | p. 51 |
Slow Start | p. 52 |
Congestion Avoidance | p. 53 |
Fast Retransmit and Fast Recovery | p. 55 |
TCP Problems | p. 57 |
Managing Congestion | p. 59 |
TCP Friendliness | p. 59 |
Classification of Congestion Control Protocols | p. 60 |
Window-Based vs. Rate-Based | p. 60 |
Unicast vs. Multicast | p. 61 |
End-to-End vs. Router-Based | p. 62 |
Concluding Comments | p. 63 |
Measuring Network Congestion | p. 65 |
Overview | p. 65 |
Drop Tail | p. 66 |
Congestion Early Warning | p. 67 |
Packet Drop Schemes | p. 68 |
Packet Marking Schemes | p. 72 |
Concluding Comments | p. 77 |
Source-Based Congestion Control Mechanisms | p. 79 |
Overview | p. 79 |
Traditional TCP | p. 80 |
TCP Modifications for Networks with Large Bandwidth Delay Products | p. 81 |
Scalable TCP (STCP) | p. 82 |
HighSpeed TCP (HSTCP) | p. 82 |
BIC | p. 84 |
CUBIC | p. 85 |
Delay-Based Congestion Control | p. 86 |
TCP Vegas | p. 87 |
FAST TCP | p. 88 |
Congestion Control for Wireless Networks | p. 89 |
TCP Westwood | p. 90 |
TCP Veno | p. 91 |
Congestion Control for Multimedia Applications | p. 92 |
Rate Adaptation Protocol (RAP) | p. 92 |
TFRC | p. 94 |
Concluding Comments | p. 95 |
Fluid Flow Model Congestion Control | p. 97 |
Overview | p. 97 |
The Fluid Flow Model | p. 98 |
Network Representation | p. 99 |
Congestion Control as a Resource Allocation Problem | p. 101 |
Dual Approach | p. 103 |
Primal Approach | p. 104 |
Utility Function Selection | p. 104 |
Open Issues | p. 106 |
Stability and Convergence | p. 106 |
Implementation Constraints | p. 107 |
Robustness | p. 107 |
Fairness | p. 108 |
Concluding Comments | p. 109 |
Adaptive Congestion Control Framework | p. 111 |
NNRC: An Adaptive Congestion Control Framework | p. 113 |
Overview | p. 113 |
Packet Switching Network System | p. 114 |
Problem Statement | p. 117 |
Throughput Improvement | p. 118 |
NNRC Framework Description | p. 120 |
Future Path Congestion Level Estimator | p. 121 |
Feasible Desired Round Trip Time Estimator | p. 122 |
Rate Control | p. 122 |
Throughput Control | p. 123 |
Concluding Comments | p. 123 |
NNRC: Rate Control Design | p. 125 |
Overview | p. 125 |
Feasible Desired Round Trip Time Estimator Design | p. 125 |
Proof of Lemma 8.1 | p. 129 |
Proof of Lemma 8.2 | p. 130 |
Rate Control Design | p. 132 |
Guaranteeing Boundness of Transmission Rate | p. 137 |
Reducing Rate in Congestion | p. 138 |
Illustrative Example | p. 140 |
Implementation Details | p. 141 |
Network Topology | p. 142 |
Normal Scenario | p. 142 |
Congestion Avoidance Scenario | p. 143 |
Concluding Comments | p. 148 |
NNRC: Throughput and Fairness Guarantees | p. 151 |
Overview | p. 151 |
Necessity for Throughput Control | p. 151 |
Problem Definition | p. 153 |
Throughput Control Design | p. 154 |
Guaranteeing Specific Bounds on the Number of Channels | p. 156 |
Reducing Channels in Congestion | p. 157 |
Illustrative Example | p. 158 |
Implementation Details | p. 159 |
Normal Scenario | p. 160 |
Congestion Avoidance Scenario | p. 163 |
Throughput Improvement | p. 163 |
Concluding Comments | p. 169 |
NNRC: Performance Evaluation | p. 171 |
Overview | p. 171 |
Network Topology | p. 172 |
Scalability | p. 174 |
Effect of Maximum Queue Length | p. 174 |
Effect of Propagation Delays | p. 176 |
Effect of Bandwidth | p. 178 |
Dynamic Response of NNRC and FAST TCP | p. 180 |
Bursty Traffic | p. 182 |
Re-Routing | p. 183 |
Non-Constant Number of Sources | p. 186 |
NNRC and FAST TCP Interfairness | p. 188 |
Synopsis of Results | p. 199 |
Concluding Comments | p. 200 |
User QoS Adaptive Control | p. 203 |
Overview | p. 203 |
Application Adaptation Architecture | p. 204 |
QoS Mapping | p. 204 |
Application QoS Control Design | p. 205 |
NNRC Source Enhanced with Application Adaptation | p. 207 |
Illustrative Example | p. 208 |
Application Adaptation Implementation Details | p. 209 |
Simulation Study | p. 210 |
Concluding Comments | p. 210 |
Appendices | p. 215 |
Dynamic Systems and Stability | p. 217 |
Vectors and Matrices | p. 217 |
Positive Definite Matrices | p. 219 |
Signals | p. 221 |
Functions | p. 223 |
Continuity | p. 223 |
Differentiation | p. 224 |
Convergence | p. 225 |
Function Properties | p. 226 |
Dynamic Systems | p. 227 |
Stability Definitions | p. 229 |
Boundedness Definitions | p. 231 |
Stability Tools | p. 232 |
Neural Networks for Function Approximation | p. 247 |
General | p. 247 |
Neural Networks Architectures | p. 249 |
Multilayer Perceptron (MLP) | p. 250 |
Radial Basis Function Networks (RBF) | p. 252 |
High-Order Neural Networks (HONN) | p. 253 |
Off-Line Training | p. 255 |
Algorithms | p. 257 |
Gradient Algorithms | p. 257 |
Least Squares | p. 261 |
Backpropagation | p. 262 |
On-Line Training | p. 263 |
Filtering Schemes | p. 263 |
Filtered Error | p. 264 |
Filtered Regressor | p. 265 |
Lyapunov-Based Training | p. 266 |
LIP Case | p. 266 |
NLIP Case | p. 266 |
Steepest Descent Training | p. 267 |
Recursive Least Squares Training | p. 268 |
Robust On-Line Training | p. 269 |
Bibliography | p. 273 |
Index | p. 301 |
Table of Contents provided by Ingram. All Rights Reserved. |
The New copy of this book will include any supplemental materials advertised. Please check the title of the book to determine if it should include any access cards, study guides, lab manuals, CDs, etc.
The Used, Rental and eBook copies of this book are not guaranteed to include any supplemental materials. Typically, only the book itself is included. This is true even if the title states it includes any access cards, study guides, lab manuals, CDs, etc.